Compressive Sensing for Ultra-Wideband Channel Estimation: on the Sparsity Assumption of Ultra-Wideband Channels

dc.contributor.author Başaran, Mehmet
dc.contributor.author Erküçük, Serhat
dc.contributor.author Erküçük, Serhat
dc.contributor.author Cirpan, Hakan Ali
dc.contributor.other Electrical-Electronics Engineering
dc.date.accessioned 2019-06-27T08:02:45Z
dc.date.available 2019-06-27T08:02:45Z
dc.date.issued 2014
dc.department Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü en_US
dc.description.abstract Due to the sparse structure of ultra-wideband (UWB) multipath channels there has been a considerable amount of interest in applying the compressive sensing (CS) theory to UWB channel estimation. The main consideration of the related studies is to propose different implementations of the CS theory for the estimation of UWB channels which are assumed to be sparse. In this study we investigate the suitability of standardized UWB channel models to be used with the CS theory. In other words we question the sparsity assumption of realistic UWB multipath channels. For that we particularly investigate the effects of IEEE 802.15.4a UWB channel models and the selection of channel resolution both on channel estimation and system performances from a practical implementation point of view. In addition we compare the channel estimation performance with the Cramer-Rao lower bound for various channel models and number of measurements. The study shows that although UWB channel models for residential environments (e.g. channel models CM1 and CM2) exhibit a sparse structure yielding a reasonable channel estimation performance channel models for industrial environments (e.g. CM8) may not be treated as having a sparse structure due to multipaths arriving densely. Furthermore it is shown that the sparsity increased by channel resolution can improve the channel estimation performance significantly at the expense of increased receiver processing. Copyright (c) 2013 John Wiley & Sons Ltd. en_US]
dc.identifier.citationcount 11
dc.identifier.doi 10.1002/dac.2548 en_US
dc.identifier.endpage 3398
dc.identifier.issn 1074-5351 en_US
dc.identifier.issn 1099-1131 en_US
dc.identifier.issn 1074-5351
dc.identifier.issn 1099-1131
dc.identifier.issue 11
dc.identifier.scopus 2-s2.0-84911959224 en_US
dc.identifier.scopusquality Q2
dc.identifier.startpage 3383 en_US
dc.identifier.uri https://hdl.handle.net/20.500.12469/679
dc.identifier.uri https://doi.org/10.1002/dac.2548
dc.identifier.volume 27 en_US
dc.identifier.wos WOS:000345306300059 en_US
dc.institutionauthor Erküçük, Serhat en_US
dc.language.iso en en_US
dc.publisher Wiley-Blackwell en_US
dc.relation.journal International Journal of Communication Systems en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.scopus.citedbyCount 14
dc.subject Compressive Sensing (CS) en_US
dc.subject Ultra-wideband (UWB) channel estimation en_US
dc.subject IEEE 802 en_US
dc.subject 15 en_US
dc.subject 4a channel models en_US
dc.subject Channel resolution en_US
dc.title Compressive Sensing for Ultra-Wideband Channel Estimation: on the Sparsity Assumption of Ultra-Wideband Channels en_US
dc.type Article en_US
dc.wos.citedbyCount 12
dspace.entity.type Publication
relation.isAuthorOfPublication 440e977b-46c6-40d4-b970-99b1e357c998
relation.isAuthorOfPublication.latestForDiscovery 440e977b-46c6-40d4-b970-99b1e357c998
relation.isOrgUnitOfPublication 12b0068e-33e6-48db-b92a-a213070c3a8d
relation.isOrgUnitOfPublication.latestForDiscovery 12b0068e-33e6-48db-b92a-a213070c3a8d

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